Don’t be alarmed: AI won’t leave half the world unemployed

Intelligent machines are good at some jobs that were once done by humans. Image credit – Shutterstock/SFC

Recent alarmist headlines this week claim artificial intelligence (AI) will put half of us out of work.

These headlines – and there were several – stem from comments by Rice University’s computer scientist Moshe Vardi who at the weekend asked what society would do when, within 30 years, machines become capable of doing almost any job a human can.

As ever, reality is likely to be far more nuanced than sensational headlines.

The most detailed study in this area came out in September 2013 from the Oxford Martin School. This report predicted that 47% of jobs in the US were under threat of automation. Similar studies have since been performed for other countries, reaching broadly similar conclusions.

Now, there’s a lot I would disagree with in the Oxford report. But, for the sake of the discussion here, let’s just suppose for a moment that the report is correct.

Even with this assumption, you cannot conclude that half of us will be unemployed in 30 or so years. The Oxford report merely estimated the number of jobs that are potentially automatable over the next few decades. There are many reasons why this will not translate into 47% unemployment.

We still want a human on the job

The report merely estimated the number of jobs that are susceptible to automation. Some of these jobs won’t be automated in practice for economical, societal, technical and other reasons.

For example, we can pretty much automate the job of an airline pilot today. Indeed, most of the time, a computer is flying your plane. But society is likely to continue to demand the reassurance of having a pilot on board even if they are just reading their iPad most of the time.

As a second example, the Oxford report gives a 94% chance for bicycle repairer to be automated. But it is likely to be very expensive and difficult to automate this job, and therefore uneconomic to do so.

We also need to consider all the new jobs that technology will create. For example, we don’t employ many printers setting type any more. But we do employ many more people in the digital equivalent, making web pages.

Of course, if you are a printer and your job is destroyed, it helps if you’re suitably educated so you can re-position yourself in one of these new industries.

Some of these jobs will only be partially automated, and automation will in fact enhance a person’s ability to do the job. For example, the Oxford report gives a 98% chance of umpiring or refereeing to be automated. But we are likely to have just as many if not more umpires and referees in the future, even if they use technologies to do their job better.

We also need to consider how the working week will change over the next few decades. Most countries in the developed world have seen the number of hours worked per week decrease significantly since the start of the industrial revolution.

In the US, the average working week has declined from around 60 hours to just 33. Other developed countries are even lower. Germans only work 26 hours per week. If these trends continue, we will need to create more jobs to replace these lost hours.

In my view, it’s hard to predict with any certainty how many of us will really be unemployed in a few decades time but I am very sceptical that it will be half of us. Society would break down well before we get to 50% unemployment.

My guess is it will be at most half of this prediction, 25% at most. This is nevertheless an immense change, and one that we need to start planning for and mitigating against today.

Toby Walsh, Professor of AI, Research Group Leader, Optimisation Research Group, Data61

This is a very naïve view of manufacturing, job creation and economics. To think that an increase in efficiency due to technological advancements wouldn’t lead to the decrease in labor hours required and an increase in effective output is nonsensical. There would be no purpose in increasing efficiency and production if you had to employ the same amount of technically trained, experienced and expensive workers.
The other point is that the participation rate of working aged people is currently around the 63%. With a large component of that workforce being currently under employed. A 20% drop in employment would theoretically mean that 50% of the working age population won’t be working.
There is also the fact that before the 1960’s when the majority of women didn’t work and the retirement age was lower there was a lot more people of working age that didn’t have to work, from an economical point of view it will be a reversion to the long term mean even without the advancements in technology. The main driving force for job creation before was an increasing population and the expense of tariffs and shipping goods from overseas. Both of these factors have improved. There is currently very little financial incentive to produce anything in Australia or the rest of the western world.
An increase in university attendance and graduation of a larger percentage of the population with technical qualifications will also mean greater competition for roles. This in turn is going to lead to a situation where work experience in your chosen field will become a premium. So those that where lucky enough to gain experience will be able to out compete those that are qualified with no or little experience. This is already the case in a lot of the sciences, engineering, HR and other business roles. It is currently very difficult to get a role now without significant up to date experience already doing that role.
If you take your geosciences example if you can increase the automation on a drill rig you could save yourself upwards of $200 an hour in labor costs. Now if you add high resolution and scientific instrumentation for scanning core samples you would eliminate a large proportion of geological jobs. Now upload your scans directly into 3D mapping software and you have eliminated more jobs. Now this is a scenario that basically need little geoscience intervention and just requires a mine engineer to look at the 3D models and plan the mine out. Your also talking about an employment sector with relatively low employment compared to the rest of the population, therefore even a 10% rise in geosciences wouldn’t cover job losses due to a 10% increase in manufacturing efficiency.
It is also being assumed that everyone has the mental and financial capacity to train in more technically complex roles. The reason that there isn’t a lot of people highly qualified in STEM fields is that they are mentally demanding. Just think of all those people you went to high school with probably the last time most people would have been in a mentally competitive environment. Not every one was capable of high functioning cognitive tasks and even some that were didn’t enjoy them.
Or even think about your parents I am sure we all see a decline in there mental and memory capacities after the age of 55. Have you ever tried to teach a parent or older worker how to use their phone, TV, the newest word processing software or PowerPoint. At some point we all start to find it harder or less interesting to learn new things.
Yes there will be new exciting technically focused roles created in the future. But for the half of the working population that are low paid, low skilled, low intelligence, unmotivated, unable to retrain or just shear unlucky they are prime candidates to lose their job to a cheaper more efficient machine. The world isn’t run by sharing caring sensitive types. It’s run by accountants, economists and managers trying to get the best return on capital for their shareholders or tax payers.

History and the hyperexponential growth of cognitive technologies argue against this Pollyannaish view. The industrial revolution replaced the need for most animal muscle power. The jobs that were left depended on human cognition directing tools and processes.

Cognitive technologies are rapidly replaceing slow and fallible human cognition with ever faster, more accurate and sophisticated electronic cognition. If this exponential trend continues for long, what will be left for messy biological systems to do??? As an evolutionary biologist interested in the roles of technology, I don’t see much future for us.